Abstract
We present algorithms for the automatic delineation of lung fields in chest radiographs. We first develop a rule-based scheme that detects lung contours using a general framework for the detection of oriented edges and ridges. This algorithm is compared to several pixel classifiers using different combinations of features. We propose a hybrid system that combines both approaches. The performance of each system is compared with interobserver variability and results available from the literature. Our hybrid scheme turns out to be accurate and robust; the accuracy is 0.969 ± 0.00803, and above 94% for all 115 test images.
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© 1999 Springer-Verlag Berlin Heidelberg
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van Ginneken, B., ter Haar Romeny, B.M. (1999). Automatic Segmentation of Lung Fields in Chest Radiographs. In: Taylor, C., Colchester, A. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI’99. MICCAI 1999. Lecture Notes in Computer Science, vol 1679. Springer, Berlin, Heidelberg. https://doi.org/10.1007/10704282_20
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DOI: https://doi.org/10.1007/10704282_20
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-66503-8
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